High-Throughput Computational Screening of Cubic Perovskites for Solid Oxide Fuel Cell Cathodes


It is a present-day challenge to design and develop oxygen permeable solid oxide fuel cell (SOFC) electrode and electrolyte materials that operate at low temperatures. Herein, by performing high-throughput density functional theory (HT-DFT) calculations, oxygen vacancy formation energy, Evac, data for a pool of all-inorganic ABO3 and AI0.5AII0.5BO3 cubic perovskites is generated. Using Evac data of perovskites, the area-specific resistance (ASR) data, which is related to both oxygen reduction reaction activity and selective oxygen ion conductivity of materials, is calculated. Screening a total of 270 chemical compositions, 31 perovskites are identified as candidates with properties that are in between state-of-the-art SOFC cathode and oxygen permeation components. In addition, an intuitive approach to estimate Evac and ASR data of complex perovskites solely by using the easy-to-access data of simple perovskites is shown, which is expected to boost future explorations on perovskite material search space for genuinely diverse energy applications.


Supplementary material

2021-03-14 - Tezsevin et.al. - High-throughput computational screening of cubic perovskites for solid oxide fuel cell cathodes - SI